{"id":"W1898892862","doi":"10.1007/s11517-015-1396-2","title":"Network analysis of human fMRI data suggests modular restructuring after simulated acquired brain injury","year":2015,"lang":"en","type":"article","venue":"Medical & Biological Engineering & Computing","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Consejo Nacional de Ciencia y Tecnología; Heart and Stroke Foundation of Canada","keywords":"Traumatic brain injury; Neurocognitive; Functional magnetic resonance imaging; Modular design; Neuroscience; Diffuse axonal injury; Physical medicine and rehabilitation; Cognition; Magnetic resonance imaging; Psychology; Medicine; Computer science; Radiology; Psychiatry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001514056,0.0002740426,0.0006584032,0.0001979827,0.0001281438,0.00003100518,0.0008655883,0.0002309295,0.00008282955],"category_scores_gemma":[0.03168416,0.0002206939,0.0001214278,0.001485515,0.000239233,0.00009719512,0.001662526,0.0003490831,0.000009009531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006539108,"about_ca_system_score_gemma":0.00003928781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003693903,"about_ca_topic_score_gemma":0.000004505818,"domain_scores_codex":[0.9970178,0.0002520273,0.0005762234,0.0008931474,0.0007000857,0.00056072],"domain_scores_gemma":[0.9938758,0.004938651,0.0001362436,0.0006763829,0.00006581592,0.0003070931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001292624,0.0001187777,0.05009011,0.00004144904,0.0003563019,0.0001705892,0.0001865907,0.9141306,0.03039871,0.0006574088,0.001202245,0.002518003],"study_design_scores_gemma":[0.000335671,0.0001800917,0.1215163,0.00008400436,0.00007740329,0.000007587701,0.00001045264,0.8758559,0.0007138909,0.0002038135,0.0007078824,0.0003070977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989216,0.0001636407,0.008842469,0.0008790969,0.0004278998,0.0001302736,0.00002316382,0.0002598512,0.00005760164],"genre_scores_gemma":[0.9976264,0.000003149143,0.0006154642,0.001274418,0.0004064191,0.000002743618,0.00004382213,0.00001915483,0.000008441209],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07142615,"threshold_uncertainty_score":0.9764724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07389026602496557,"score_gpt":0.3135209199027187,"score_spread":0.2396306538777532,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}